In [1]:
from IPython.display import HTML

HTML('''<script>
code_show=true; 
function code_toggle() {
 if (code_show){
 $('div.input').hide();
 } else {
 $('div.input').show();
 }
 code_show = !code_show
} 
$( document ).ready(code_toggle);
</script>
<form action="javascript:code_toggle()"><input type="submit" value="Click here to toggle on/off the raw code."></form>''')
Out[1]:
In [2]:
from IPython.display import HTML

HTML('''<script> $('div .input').hide()''')
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In [10]:
bar_plots = [
    go.Bar(x = df['Year'], y = df['Ave. Usage/P (kWh/p)'],name='Total Consumption (kWh)')
           ]
layout = go.Layout(
title=go.layout.Title(text='Monthly Average Person Electricity Consumption In Respective Year',x=0.5),
yaxis_title='Usage (kWh/person)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
#fig.show()
In [11]:
bar_plots = [
    go.Bar(x = df['Year'], y = df['Ave. Usage/A (kWh/m2)'],name='Total Consumption (kWh)')
           ]
layout = go.Layout(
title=go.layout.Title(text='Monthly Average Electricity Consumption/Area In Respective Year',x=0.5),
yaxis_title='Usage (kWh/m2)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
In [12]:
bar_plots = [
    go.Bar(x = df['Year'], y = df['Total Usage (kWh)'],name='Total Consumption (kWh)'),
    go.Bar(x = df['Year'], y = df['Total Amount (RM)'],name='Total Amount (RM)')
           ]
layout = go.Layout(
title=go.layout.Title(text='Annual Electricity Consumption (kWh) & Amount (RM)',x=0.5),
yaxis_title='Usage (kWh)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()

Detail of Electriciy Consumption and Amount for Respective Year

In [13]:
bar_plots = [
    go.Bar(x = df1[2014], y = df1['Usage (kWh)'],name=2014),
    go.Bar(x = df2[2015], y = df2['Usage (kWh)'],name=2015),
    go.Bar(x = df3[2016], y = df3['Usage (kWh)'],name=2016),
    go.Bar(x = df4[2017], y = df4['Usage (kWh)'],name=2017),
    go.Bar(x = df5[2018], y = df5['Usage (kWh)'],name=2018),
    go.Bar(x = df6[2019], y = df6['Usage (kWh)'],name=2019),
    go.Bar(x = df7[2020], y = df7['Usage (kWh)'],name=2020),
    go.Bar(x = df8[2021], y = df8['Usage (kWh)'],name=2021),
    go.Bar(x = df9[2022], y = df9['Usage (kWh)'],name=2022)
           ]
layout = go.Layout(
title=go.layout.Title(text='Monthly Electricity Consumption (kWh)',x=0.5),
yaxis_title='Usage (kWh)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()
In [14]:
bar_plots = [
    go.Bar(x = df1[2014], y = df1['Amount (RM)'],name=2014),
    go.Bar(x = df2[2015], y = df2['Amount (RM)'],name=2015),
    go.Bar(x = df3[2016], y = df3['Amount (RM)'],name=2016),
    go.Bar(x = df4[2017], y = df4['Amount (RM)'],name=2017),
    go.Bar(x = df5[2018], y = df5['Amount (RM)'],name=2018),
    go.Bar(x = df6[2019], y = df6['Amount (RM)'],name=2019),
    go.Bar(x = df7[2020], y = df7['Amount (RM)'],name=2020),
    go.Bar(x = df8[2021], y = df8['Amount (RM)'],name=2021),
    go.Bar(x = df9[2022], y = df9['Amount (RM)'],name=2022)
           ]
layout = go.Layout(
title=go.layout.Title(text='Monthly Electricity Amount (RM)',x=0.5),
yaxis_title='Amount (RM)',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()

Detail of Consumption (kWh) and Amount (RM) for Every Years From 2014 to 2020

In [15]:
df1['kWh/person'] = df1['Usage (kWh)']/5
df2['kWh/person'] = df2['Usage (kWh)']/5
df3['kWh/person'] = df3['Usage (kWh)']/5
df4['kWh/person'] = df4['Usage (kWh)']/5
df5['kWh/person'] = df5['Usage (kWh)']/5
df6['kWh/person'] = df6['Usage (kWh)']/5
df7['kWh/person'] = df7['Usage (kWh)']/5
df8['kWh/person'] = df8['Usage (kWh)']/5
df9['kWh/person'] = df9['Usage (kWh)']/5
display_side_by_side(df1, df2, df3)
2014 Usage (kWh) Amount (RM) kWh/person
0 Jan 261 63.98 52.2
1 Feb 288 70.56 57.6
2 Mac 348 101.77 69.6
3 Apr 263 64.64 52.6
4 May 350 102.80 70.0
5 Jun 324 89.38 64.8
6 Jul 346 100.74 69.2
7 Aug 268 66.31 53.6
8 Sep 292 74.33 58.4
9 Oct 267 65.98 53.4
10 Nov 301 77.52 60.2
11 Dec 337 86.34 67.4
2015 Usage (kWh) Amount (RM) kWh/person
0 Jan 254 61.64 50.8
1 Feb 347 86.90 69.4
2 Mac 276 68.98 55.2
3 Apr 309 81.64 61.8
4 May 301 77.52 60.2
5 Jun 273 67.98 54.6
6 Jul 405 103.84 81.0
7 Aug 238 56.29 47.6
8 Sep 295 75.33 59.0
9 Oct 266 65.64 53.2
10 Nov 321 81.69 64.2
11 Dec 284 71.66 56.8
2016 Usage (kWh) Amount (RM) kWh/person
0 Jan 246 58.96 49.2
1 Feb 399 120.01 79.8
2 Mac 530 188.20 106.0
3 Apr 465 162.14 93.0
4 May 494 177.10 98.8
5 Jun 342 98.67 68.4
6 Jul 305 79.58 61.0
7 Aug 409 125.46 81.8
8 Sep 336 87.80 67.2
9 Oct 378 117.25 75.6
10 Nov 286 72.32 57.2
11 Dec 308 78.16 61.6
In [16]:
display_side_by_side(df4, df5, df6)
2017 Usage (kWh) Amount (RM) kWh/person
0 Jan 427 142.53 85.4
1 Feb 390 123.44 78.0
2 Mac 448 153.37 89.6
3 Apr 441 149.76 88.2
4 May 361 108.48 72.2
5 Jun 393 124.99 78.6
6 Jul 339 91.97 67.8
7 Aug 383 119.83 76.6
8 Sep 399 122.93 79.8
9 Oct 406 131.70 81.2
10 Nov 405 131.18 81.0
11 Dec 327 90.93 65.4
2018 Usage (kWh) Amount (RM) kWh/person
0 Jan 342 98.67 68.4
1 Feb 455 149.20 91.0
2 Mac 426 142.02 85.2
3 Apr 419 138.40 83.8
4 May 490 175.04 98.0
5 Jun 315 78.88 63.0
6 Jul 357 106.41 71.4
7 Aug 412 134.79 82.4
8 Sep 389 115.14 77.8
9 Oct 358 106.93 71.6
10 Nov 368 112.09 73.6
11 Dec 309 81.64 61.8
2019 Usage (kWh) Amount (RM) kWh/person
0 Jan 370 113.12 74.0
1 Feb 444 151.30 88.8
2 Mac 399 130.15 79.8
3 Apr 373 116.50 74.6
4 May 413 137.45 82.6
5 Jun 285 72.00 57.0
6 Jul 366 112.85 73.2
7 Aug 280 70.30 56.0
8 Sep 348 103.40 69.6
9 Oct 336 97.10 67.2
10 Nov 323 90.30 64.6
11 Dec 312 84.50 62.4
In [17]:
display_side_by_side(df7, df8, df9)
2020 Usage (kWh) Amount (RM) kWh/person
0 Jan 355 107.05 71.0
1 Feb 314 85.55 62.8
2 Mac 350 104.45 70.0
3 Apr 350 96.35 70.0
4 May 350 88.80 70.0
5 Jun 1221 164.40 244.2
6 Jul 368 112.10 73.6
7 Aug 344 99.70 68.8
8 Sep 360 107.96 72.0
9 Oct 336 82.55 67.2
10 Nov 391 107.05 78.2
11 Dec 341 84.80 68.2
2021 Usage (kWh) Amount (RM) kWh/person
0 Jan 322 79.55 64.4
1 Feb 378 111.55 75.6
2 Mac 378 111.55 75.6
3 Apr 361 103.00 72.2
4 May 357 100.95 71.4
5 Jun 393 119.15 78.6
6 Jul 361 103.00 72.2
7 Aug 436 122.28 87.2
8 Sep 396 108.60 79.2
9 Oct 444 136.60 88.8
10 Nov 404 124.65 80.8
11 Dec 366 105.50 73.2
2022 Usage (kWh) Amount (RM) kWh/person
0 Jan 359.0 102.00 71.8
1 Feb 323.0 83.85 64.6
2 Mac 384.0 114.60 76.8
3 Apr 460.0 152.91 92.0
4 May NaN NaN NaN
5 Jun NaN NaN NaN
6 Jul NaN NaN NaN
7 Aug NaN NaN NaN
8 Sep NaN NaN NaN
9 Oct NaN NaN NaN
10 Nov NaN NaN NaN
11 Dec NaN NaN NaN
In [18]:
bar_plots = [
    go.Bar(x = df1[2014], y = df1['kWh/person'],name=2014),
    go.Bar(x = df2[2015], y = df2['kWh/person'],name=2015),
    go.Bar(x = df3[2016], y = df3['kWh/person'],name=2016),
    go.Bar(x = df4[2017], y = df4['kWh/person'],name=2017),
    go.Bar(x = df5[2018], y = df5['kWh/person'],name=2018),
    go.Bar(x = df6[2019], y = df6['kWh/person'],name=2019),
    go.Bar(x = df7[2020], y = df7['kWh/person'],name=2020),
    go.Bar(x = df8[2021], y = df8['kWh/person'],name=2021),
    go.Bar(x = df9[2022], y = df9['kWh/person'],name=2022)
           ]
layout = go.Layout(
title=go.layout.Title(text='Monthly kwh/person Usage',x=0.5),
yaxis_title='kWh/person',xaxis_tickmode='array')
fig = go.Figure(data=bar_plots, layout=layout)
fig.show()

Details of Monthly Electricity Usage

In [19]:
px.bar(df1, x = 2014, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2014, color_continuous_scale=px.colors.sequential.Viridis)
In [20]:
px.bar(df2, x = 2015, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2015, color_continuous_scale=px.colors.sequential.Viridis)
In [21]:
px.bar(df3, x = 2016, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2016, color_continuous_scale=px.colors.sequential.Viridis)
In [22]:
px.bar(df4, x = 2017, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2017, color_continuous_scale=px.colors.sequential.Viridis)
In [23]:
px.bar(df5, x = 2018, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2018, color_continuous_scale=px.colors.sequential.Viridis)
In [24]:
px.bar(df6, x = 2019, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2019, color_continuous_scale=px.colors.sequential.Viridis)
In [25]:
px.bar(df7, x = 2020, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2020, color_continuous_scale=px.colors.sequential.Viridis)
In [26]:
px.bar(df8, x = 2021, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2021, color_continuous_scale=px.colors.sequential.Viridis)
In [27]:
px.bar(df9, x = 2022, y = 'Usage (kWh)', title = 'Electricity Usage Annually', color=2022, color_continuous_scale=px.colors.sequential.Viridis)

Details of Monthly Electricity Cost

In [28]:
px.bar(df1, x = 2014, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2014, color_continuous_scale=px.colors.sequential.Viridis)
In [29]:
px.bar(df2, x = 2015, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2015, color_continuous_scale=px.colors.sequential.Viridis)
In [30]:
px.bar(df3, x = 2016, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2016, color_continuous_scale=px.colors.sequential.Viridis)
In [31]:
px.bar(df4, x = 2017, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2017, color_continuous_scale=px.colors.sequential.Viridis)
In [32]:
px.bar(df5, x = 2018, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2018, color_continuous_scale=px.colors.sequential.Viridis)
In [33]:
px.bar(df6, x = 2019, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2019, color_continuous_scale=px.colors.sequential.Viridis)
In [34]:
px.bar(df7, x = 2020, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2020, color_continuous_scale=px.colors.sequential.Viridis)
In [35]:
px.bar(df8, x = 2021, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2021, color_continuous_scale=px.colors.sequential.Viridis)
In [36]:
px.bar(df9, x = 2022, y = 'Amount (RM)', title = 'Electricity Payment Annually', color=2022, color_continuous_scale=px.colors.sequential.Viridis)

Note: This report is prepared by Zahiruddin Zahidanishah. This report is only for educational purposed and shall not be used for any commercial purposed.